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TopoX: A Suite of Python Packages for Machine Learning on Topological Domains

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arxiv 2402.02441 v5 pith:IUH6ZMBS submitted 2024-02-04 cs.LG cs.AIcs.MSstat.CO

classification cs.LGcs.AIcs.MSstat.CO
keywords domainstopologicaltopoxcomputinggithubhigher-orderhttpslearning
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We introduce TopoX, a Python software suite that provides reliable and user-friendly building blocks for computing and machine learning on topological domains that extend graphs: hypergraphs, simplicial, cellular, path and combinatorial complexes. TopoX consists of three packages: TopoNetX facilitates constructing and computing on these domains, including working with nodes, edges and higher-order cells; TopoEmbedX provides methods to embed topological domains into vector spaces, akin to popular graph-based embedding algorithms such as node2vec; TopoModelX is built on top of PyTorch and offers a comprehensive toolbox of higher-order message passing functions for neural networks on topological domains. The extensively documented and unit-tested source code of TopoX is available under MIT license at https://pyt-team.github.io/}{https://pyt-team.github.io/.

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  1. Cosmology with Topological Deep Learning

    astro-ph.CO 2025-05 conditional novelty 6.0 of 10

    Topological neural networks using tetrahedra, clusters and hyperedges built from halo catalogs lower inference error on Omega_m by 22% and on sigma_8 by up to 60% versus graph neural networks on Quijote.

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